The invention relates to detecting trends in machine operation and generating alarms when these trends indicate a potential machine malfunction or other alarm conditions.
Early notification of malfunctions or other alarm conditions in a machine or process assists operators to react to and cure the malfunction or condition. Early warning of malfunctions is particularly important for machines and processes in nuclear power plants, oil refineries, conventional power plants, pipeline pumping stations, manufacturing facilities, aircraft engines and in other critical facilities and applications. Early detection of a malfunction may allow an operator to prevent extensive damage to machines, stop a potentially dangerous condition, and maintain efficient and continuous operation.
Sensors are well known that monitor various machine conditions, e.g., vibration, temperature, flow pressure, lubrication flow and power output and/or demand. Some sensors average data over a period of time to mitigate effects of an erroneous sensor reading or short aberration in a machine condition. Based on the data from the sensors, machine controllers determine whether a malfunction has occurred or if conditions in the machine are ripe for a malfunction. These controllers may apply threshold levels to sensor data to determine if the machine condition exceeds a desired level. If the threshold level is exceeded by the sensor data, then the controller may generate an alarm condition. If the threshold level is set too high, the machine may have already malfunctioned and be damaged when the controller issues an alarm. If the threshold level is too low, the controller may issue too many false alarms. Accordingly, there is a need for algorithms to detect machine and process conditions that accurately identify potential malfunction conditions and provide early notice of such conditions.